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Dictionary based estimation of distribution algorithms
2007 International Symposium on Communications and Information Technologies, 2007This paper proposes a new algorithm in the field of estimation of distribution algorithms. The proposed algorithm combines a data compression algorithm to extract a model into the dictionary. This dictionary is used as a part of the generator to generate the better next generation of population.
null Chalermsub Sangkavichitr +1 more
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Estimation of particle swarm distribution algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009This paper presents a framework of estimation of particle swarm distribution algorithms (EPSDAs). The aim lies in effectively combining particle swarm optimization (PSO) with estimation of distribution algorithms (EDAs) without losing on their unique features.
Chang Wook Ahn, Hyun-Tae Kim
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Drift and Scaling in Estimation of Distribution Algorithms
Evolutionary Computation, 2005This paper considers a phenomenon in Estimation of Distribution Algorithms (EDA) analogous to drift in population genetic dynamics. Finite population sampling in selection results in fluctuations which get reinforced when the probability model is updated.
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Chaos elitism estimation of distribution algorithm
Fifth International Conference on Intelligent Control and Information Processing, 2014Estimation of distribution algorithm (EDA) is a kind of EAs, which is based on the technique of probabilistic model and sampling. This paper presents a chaos elitism EDA to improve the performance of traditional EDA to solve high dimensional optimization problems. The famous elitism strategy is introduced to maintain a good convergent performance.
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Reinforcement Learning Estimation of Distribution Algorithm
2003This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions to generate a new population of solutions. We call it Reinforcement Learning Estimation of Distribution Algorithm (RELEDA).
Topon Kumar Paul, Hitoshi Iba
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Memetic Algorithms of Graph-Based Estimation of Distribution Algorithms
2015This paper constitutes Memetic Algorithms of the graph-based Estimation of Distribution algorithms which have been proposed by us previously. The graph-based EDA employs graph-kernels to estimate the probabilistic distributions of individuals, i.e., graphs. In this paper, a greedy-search is introduced into the graph-based EDA.
Kenta Maezawa, Hisashi Handa
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Continuous Gaussian Estimation of Distribution Algorithm
2013Metaheuristics algorithms such as Estimation of Distribution Algorithms use probabilistic modeling to generate candidate solutions in optimization problems. The probabilistic presentation and modeling allows the algorithms to climb the hills in the search space.
Shahram Shahraki +1 more
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Estimation of Distribution Algorithms with Mutation
2005The Estimation of Distribution Algorithms are a class of evolutionary algorithms which adopt probabilistic models to reproduce the genetic information of the next generation, instead of conventional crossover and mutation operations. In this paper, we propose new EDAs which incorporate mutation operator to conventional EDAs in order to keep the ...
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Diversity Loss in General Estimation of Distribution Algorithms
2006A very general class of EDAs is defined, on which universal results on the rate of diversity loss can be derived. This EDA class, denoted SML-EDA, requires two restrictions: 1) in each generation, the new probability model is build using only data sampled from the current probability model; and 2) maximum likelihood is used to set model parameters ...
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